基于多种群搜索策略粒子群算法的舰船消磁优化

Optimization of ship degaussing system based on multi-population PSO

在现代舰船消磁系统中,消磁线圈数目不断增加,已经难以用常规方法进行调整。为解决这一问题,将一种基于多种群搜索策略的粒子群算法用于舰船消磁系统的优化。利用多种群协作来压缩搜索空间,快速提高得到全局最优解的概率。利用测得的船体原始磁场和各消磁线圈的磁场效果,以舰船残余磁场均方根最小和峰值最小为目标函数,用该算法对系统进行优化调整,并给出优化调整的数学模型及优化结果。仿真结果表明该方法可以高效、快速地决策出消磁电流的大小和方向,对提高消磁质量、缩短消磁时间是十分重要的。

Conventional methods are more and more difficult to adjust the modern ship degaussing system due to degaussing winding numbers being increased continually in it.So a kind of multi-population particle swarm algorithm is applied to optimize ship degaussing system.Multi-population collaboration can compress search space to improve the probability of searching global optimization solution.Using ship initial magnetic fields and degaussing winding magnetic effect measured,the system is optimized by this algorithm regarding minimal root mean square and peak of system remains magnetic fields as objective functions.Simulation results show that this method can judge the amount and direction of degaussing current quickly,which improves degaussing quality and reduce degaussing time effectively.